About this role
About Orakl Oncology
At Orakl Oncology, we are accelerating the development of oncology treatments. Today, fewer than 5% of new cancer drugs succeed in clinical trials. Clearly, new methods are needed.
We combine cutting-edge biology and AI to build the next generation of insight platform with the world’s largest cohort of patient tumor avatars. These avatars fuel our AI-powered predictive engine, helping to anticipate clinical trial outcomes, validate therapies, and uncover new drug candidates. By generating multimodal, real-world data, we deliver insights that consistently outperform existing solutions.
Our mission is simple yet ambitious: to bring more effective treatments to patients and to make drug development smarter, faster, and more personalized. We collaborate with leading hospitals, research institutes and pharmaceutical companies worldwide. Backed by tier one investors, we are a fast-growing, mission-driven startup at the intersection of science and technology.
Our internal R&D programs generate a steady stream of open questions, about tumor biology, about the patient-derived models we generate across indications, and about how those models behave under drug exposure. Answering these questions takes real analytical firepower. These questions sit in different programmes across the company and run on different timelines.
What you'll do
You'll work alongside domain experts in cell biology, translational science, organoid establishment, drug screening, and data engineering. You will be part of the team that decides how the question gets tackled, from experimental design through interpretation.
Turn analyses into actionable answers that keep programme and product decisions moving, with reasoning solid enough to hold up to scrutiny.
Inform key programs (e.g. protocol design, commercial readiness) through deep cross analysis of molecular, functional and clinical data
You will communicate your results to internal and external stakeholders: publication-quality figures, panels and supporting narrative, extending to posters, presentations or manuscripts where relevant.
What we're looking for
We are looking for someone who's comfortable working on complex biological questions across different therapeutic areas and drug development programs. You will own analysis and interpretation. The ideal candidate is creative, driven, fast, rigorous and autonomous.
You will be tackling complex internal R&D subjects that are actively slowing down cancer research. Your findings will impact the field and your work is expected to reach leading scientists via international conferences and peer-reviewed papers.
Must have
PhD in Computational Biology, bioengineering or any related field, 2 to 3 years analyzing complex biological data in a research or biotech setting is a plus.
Strong experience with molecular data: You analyse omics data (transcriptomics, genomics) within the context of cell biology, translational science, organoid establishment, drug screening…
Interdisciplinary mindset: You quickly understand the context and framework within teams outside of your area of expertise. You are comfortable working in an interdisciplinary setting with biologists, lab-based scientists and engineers.
Structured communication: You communicate research findings clearly through well-documented code, notebooks, written summaries, and presentations. For example, you can highlight key figures or publications where you drove the computational biology.
Real interest in cancer biology: You don't need to arrive as an expert: there's considerable depth around you and you'll absorb a great deal of it. But you should find the cancer biology genuinely interesting, and be the sort of person who goes the extra mile to understand what happens behind the result.
Strong programming skills: Python and fluency in the scientific coding stack.
Fluent in English: We are an interdisciplinary and multicultural team working in English.
Nice to have
Strong experience working with experimentalists.
Comfortable holding two or three analyses in parallel without losing track of either.
Experience in working with or analyzing data generated from sophisticated patient-derived cellular models (e.g. PDOs, PDXOs).
Industry experience where your analyses fed real go/no-go decisions.
What we offer
Mission: work in a cutting-edge environment, on the forefront of cancer research.
Role: be in a high-impact research role at the core of a distinctive oncology discovery platform, where you will have access to rare PDO multi-omics and functional datasets, and a dedicated engineering counterpart to turn your methods into durable building blocks.
Impact: participate and have ownership in a fast-growing, multi-faceted project at the early stage of a growing start-up, with the opportunity to shape it; a role where your technical expertise will have a tangible impact on patient outcomes.
Team: join a collaborative, multidisciplinary team where you’ll work alongside stellar clinicians, biologists, and engineers towards a common mission.
Interview Process
HR Call: Getting to know each other, aligning on expectations and context.
Technical Deep Dive: A deep conversation on your experience with production data pipelines, data modeling, and scientific data processing.
Technical Case: A system-design and problem-solving exercise representative of the real wet-lab data challenges you'll face at Orakl.
Reference Call: A conversation with one or two people you've worked with closely.
Founder Interview: A final discussion with our founders on vision, culture fit, and mutual ambitions.
Orakl Oncology is committed to diversity and equal opportunity. All qualified applications will be considered.